TiK-means: K-means clustering for skewed groups

04/21/2019

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by   Nicholas S. Berry, et al.

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The K-means algorithm is extended to allow for partitioning of skewed groups. Our algorithm is called TiK-Means and contributes a K-means type algorithm that assigns observations to groups while estimating their skewness-transformation parameters. The resulting groups and transformation reveal general-structured clusters that can be explained by inverting the estimated transformation. Further, a modification of the jump statistic chooses the number of groups. Our algorithm is evaluated on simulated and real-life datasets and then applied to a long-standing astronomical dispute regarding the distinct kinds of gamma ray bursts.